AIMC Topic: Emotions

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EEG-Based Emotion Recognition: A State-of-the-Art Review of Current Trends and Opportunities.

Computational intelligence and neuroscience
Emotions are fundamental for human beings and play an important role in human cognition. Emotion is commonly associated with logical decision making, perception, human interaction, and to a certain extent, human intelligence itself. With the growing ...

Deep-Net: A Lightweight CNN-Based Speech Emotion Recognition System Using Deep Frequency Features.

Sensors (Basel, Switzerland)
Artificial intelligence (AI) and machine learning (ML) are employed to make systems smarter. Today, the speech emotion recognition (SER) system evaluates the emotional state of the speaker by investigating his/her speech signal. Emotion recognition i...

Emotion Recognition in Immersive Virtual Reality: From Statistics to Affective Computing.

Sensors (Basel, Switzerland)
Emotions play a critical role in our daily lives, so the understanding and recognition of emotional responses is crucial for human research. Affective computing research has mostly used non-immersive two-dimensional (2D) images or videos to elicit em...

Single-trial EEG emotion recognition using Granger Causality/Transfer Entropy analysis.

Journal of neuroscience methods
BACKGROUND: Emotion recognition has been studied for decades, but the classification accuracy needs to be improved.

Eye-Tracking Analysis for Emotion Recognition.

Computational intelligence and neuroscience
This article reports the results of the study related to emotion recognition by using eye-tracking. Emotions were evoked by presenting a dynamic movie material in the form of 21 video fragments. Eye-tracking signals recorded from 30 participants were...

End-to-End Training for Compound Expression Recognition.

Sensors (Basel, Switzerland)
For a long time, expressions have been something that human beings are proud of. That is an essential difference between us and machines. With the development of computers, we are more eager to develop communication between humans and machines, espec...

Emotion Assessment Using Feature Fusion and Decision Fusion Classification Based on Physiological Data: Are We There Yet?

Sensors (Basel, Switzerland)
Emotion recognition based on physiological data classification has been a topic of increasingly growing interest for more than a decade. However, there is a lack of systematic analysis in literature regarding the selection of classifiers to use, sens...

Emotional EEG classification using connectivity features and convolutional neural networks.

Neural networks : the official journal of the International Neural Network Society
Convolutional neural networks (CNNs) are widely used to recognize the user's state through electroencephalography (EEG) signals. In the previous studies, the EEG signals are usually fed into the CNNs in the form of high-dimensional raw data. However,...

CNN and LSTM-Based Emotion Charting Using Physiological Signals.

Sensors (Basel, Switzerland)
Novel trends in affective computing are based on reliable sources of physiological signals such as Electroencephalogram (EEG), Electrocardiogram (ECG), and Galvanic Skin Response (GSR). The use of these signals provides challenges of performance impr...

DE-CNN: An Improved Identity Recognition Algorithm Based on the Emotional Electroencephalography.

Computational and mathematical methods in medicine
In the past few decades, identification recognition based on electroencephalography (EEG) has received extensive attention to resolve the security problems of conventional biometric systems. In the present study, a novel EEG-based identification syst...